Adaptive and Personalized Learning Based on Students’ Cognitive Characteristics

Working memory capacity (WMC) is a cognitive characteristic that affects students’ learning behaviors to perform complex cognitive tasks. However, WMC is very limited and can be easily overloaded in learning activities. Considering students’WMC through personalized learning materials and activities helps in avoiding cognitive overload and therefore positively affects students’ learning. However, in order to consider students’ WMC in the learning process, an approach is needed to identify students’ WMC without any additional efforts from students. To address this problem, we introduce a general approach to automatically identify WMC from students’ behavior in a learning system. Our approach is generic and designed to work with different learning systems. Furthermore, by knowing students’ WMC, a learning system can provide teachers meaningful recommendations to support students with low and high WMC. Accordingly, we created a recommendation mechanism that provides recommendations based on the guidelines of cognitive load theory. These recommendations are intended to assist in presentation T.-W. Chang (&) J. Kurcz M.M. El-Bishouty Kinshuk S. Graf Athabasca University, 1 University Drive Athabasca, AB T9S 3A3 Edmonton, Alberta, Canada e-mail: [email protected] J. Kurcz e-mail: [email protected] M.M. El-Bishouty e-mail: [email protected] Kinshuk e-mail: [email protected] S. Graf e-mail: [email protected] T.-W. Chang M.M. El-Bishouty Kinshuk S. Graf 1200, 10011-109 Street, Edmonton AB T5J 3S8, Canada J. Kurcz 1324 Hansen Cres, Windsor, ON N8W 5M8, Canada © Springer-Verlag Berlin Heidelberg 2015 Kinshuk and R. Huang (eds.), Ubiquitous Learning Environments and Technologies, Lecture Notes in Educational Technology, DOI 10.1007/978-3-662-44659-1_5 77 [email protected] of information in order to reduce working memory overload. Information about WMC is also the basis for designing adaptive systems that can automatically provide students with individualized support based on their WMC.